


"""simple docstring"""



from ....configuration_utils import PretrainedConfig
from ....utils import logging


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{
    '''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
        '''https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'''
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}







class    __a						( _UpperCAmelCase							):
				lowerCamelCase     :       Optional[int]			       ='trajectory_transformer'
				lowerCamelCase     :       Tuple			       =['past_key_values']
				lowerCamelCase     :       Tuple			       ={
				    'hidden_size': 'n_embd',
				    'num_attention_heads': 'n_head',
				    'num_hidden_layers': 'n_layer',
				}







				def __init__( self      ,	UpperCAmelCase=100      ,	UpperCAmelCase=5      ,	UpperCAmelCase=1      ,	UpperCAmelCase=1      ,	UpperCAmelCase=249      ,	UpperCAmelCase=6      ,	UpperCAmelCase=17      ,	UpperCAmelCase=25      ,	UpperCAmelCase=4      ,	UpperCAmelCase=4      ,	UpperCAmelCase=128      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=0.0_0_0_6      ,	UpperCAmelCase=512      ,	UpperCAmelCase=0.0_2      ,	UpperCAmelCase=1E-1_2      ,	UpperCAmelCase=1      ,	UpperCAmelCase=True      ,	UpperCAmelCase=1      ,	UpperCAmelCase=5_0256      ,	UpperCAmelCase=5_0256      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					lowerCAmelCase_      							=			vocab_size
					lowerCAmelCase_      							=			action_weight
					lowerCAmelCase_      							=			reward_weight
					lowerCAmelCase_      							=			value_weight
					lowerCAmelCase_      							=			max_position_embeddings
					lowerCAmelCase_      							=			block_size
					lowerCAmelCase_      							=			action_dim
					lowerCAmelCase_      							=			observation_dim
					lowerCAmelCase_      							=			transition_dim
					lowerCAmelCase_      							=			learning_rate
					lowerCAmelCase_      							=			n_layer
					lowerCAmelCase_      							=			n_head
					lowerCAmelCase_      							=			n_embd
					lowerCAmelCase_      							=			embd_pdrop
					lowerCAmelCase_      							=			attn_pdrop
					lowerCAmelCase_      							=			resid_pdrop
					lowerCAmelCase_      							=			initializer_range
					lowerCAmelCase_      							=			layer_norm_eps
					lowerCAmelCase_      							=			kaiming_initializer_range
					lowerCAmelCase_      							=			use_cache
					super().__init__(pad_token_id=__UpperCamelCase      ,	bos_token_id=__UpperCamelCase      ,	eos_token_id=__UpperCamelCase      ,	**__UpperCamelCase   )

"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a       :						List[Any]       		=		logging.get_logger(__name__)

a       :						str       		=		{
    '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/config.json''',
    '''umberto-commoncrawl-cased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'''
    ),
    '''umberto-wikipedia-uncased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'''
    ),
}




class 		a_    (			_UpperCAmelCase						):
    a   :					Any			     =					'camembert'







    def __init__(      self      :							Dict  ,       __UpperCamelCase      :							Union[str, Any]=3_05_22  ,       __UpperCamelCase      :							Tuple=7_68  ,       __UpperCamelCase      :							Optional[Any]=12  ,       __UpperCamelCase      :							int=12  ,       __UpperCamelCase      :							int=30_72  ,       __UpperCamelCase      :							int="gelu"  ,       __UpperCamelCase      :							Dict=0.1  ,       __UpperCamelCase      :							Dict=0.1  ,       __UpperCamelCase      :							List[Any]=5_12  ,       __UpperCamelCase      :							Optional[int]=2  ,       __UpperCamelCase      :							Dict=0.0_2  ,       __UpperCamelCase      :							Optional[int]=1e-12  ,       __UpperCamelCase      :							Optional[Any]=1  ,       __UpperCamelCase      :							int=0  ,       __UpperCamelCase      :							Optional[int]=2  ,       __UpperCamelCase      :							Optional[int]="absolute"  ,       __UpperCamelCase      :							int=True  ,       __UpperCamelCase      :							Dict=None  ,       **__UpperCamelCase      :							List[str]  ,       )		->Union[str, Any]:






        '''simple docstring'''






        super().__init__(pad_token_id=__UpperCamelCase  ,       bos_token_id=__UpperCamelCase  ,       eos_token_id=__UpperCamelCase  ,       **__UpperCamelCase  )

        _UpperCAmelCase        = vocab_size
        _UpperCAmelCase        = hidden_size
        _UpperCAmelCase        = num_hidden_layers
        _UpperCAmelCase        = num_attention_heads
        _UpperCAmelCase        = hidden_act
        _UpperCAmelCase        = intermediate_size
        _UpperCAmelCase        = hidden_dropout_prob
        _UpperCAmelCase        = attention_probs_dropout_prob
        _UpperCAmelCase        = max_position_embeddings
        _UpperCAmelCase        = type_vocab_size
        _UpperCAmelCase        = initializer_range
        _UpperCAmelCase        = layer_norm_eps
        _UpperCAmelCase        = position_embedding_type
        _UpperCAmelCase        = use_cache
        _UpperCAmelCase        = classifier_dropout







class 		a_    (			_UpperCAmelCase						):







    @property
    def   _snake_case       (      self      :							Optional[int]  )		->Mapping[str, Mapping[int, str]]:






        '''simple docstring'''






        if self.task == "multiple-choice":
            _UpperCAmelCase        = {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
            _UpperCAmelCase        = {0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
            ]  )